中圖分類號： TP391.41
文獻標識碼： A
DOI： 10.19358/j.issn.2096-5133.2021.05.007
引用格式： 吳劍，吳曉紅，何小海，等. 基于NSST和NLMF的多聚焦圖像融合[J].信息技術與網絡安全，2021，40(5)：39-44.

Multi-focus image fusion based on NSST and NLMF

Abstract： In order to further improve the information richness, edge clarity and visual effect of the fused image, a multi-focus image fusion algorithm based on non-downsampling shear wave transform(NSST) combined with non-local mean filtering(NLMF) was designed. Firstly, the source image was multi-scale and multi-directionally decomposed by NSST transform to obtain high and low frequency subband coefficients. Secondly, the improved Sum Modified Laplacian and the non-local mean filter fusion method were used for the low-frequency subband coefficients to construct the fusion weights of low-frequency subband coefficient; For the high-frequency subband coefficients, fusion rules based on the combination of spatial frequency and energy based on correlation coefficients were used, and then phase consistency rules were added to construct the fusion weights of high-frequency subband coefficient; Finally, the final fusion image was obtained by inverse NSST transformation. The experimental results from three sets of different focused images show that: Whether the algorithm in this paper is in subjective vision or objective evaluation, the information retention and visual clarity of the fusion image′s contour and texture have been improved.

Key words : multi-focus image fusion；non-local mean filtering；phase consistency；correlation coefficient